The present invention relates generally to the field of medical imaging and particularly to the field of volumetric medical imaging. Specifically, the invention relates to a technique for partitioning an imaged volume into sub-volumes, which may each be processed according to their anatomical landscape.
Volumetric medical imaging technologies use a variety of techniques to gather three-dimensional information about the body. For example, Computed Tomography (CT) imaging system measure the attenuation of X-ray beams passed through a patient from numerous angles. Based upon these measurements, a computer is able to reconstruct images of the portions of a patient's body responsible for the radiation attenuation. As will be appreciated by those skilled in the art, these images are based upon separate examination of a series of angularly displaced cross sections. It should be pointed out that a CT system produces data that represent the distribution of linear attenuation coefficients of the scanned object. The data are then reconstructed to produce an image which is typically displayed on a cathode ray tube, and may be printed or reproduced on film.
Likewise, Magnetic Resonance Imaging (MRI) systems are ubiquitous in the field of volumetric medical imaging. In general, MRI examinations are based on the interactions among a primary magnetic field, a radiofrequency (rf) magnetic field and time varying magnetic gradient fields with nuclear spins within the subject of interest. Specific nuclear components, such as hydrogen nuclei in water molecules, have characteristic behaviors in response to external magnetic fields. The precession of spins of such nuclear components can be influenced by manipulation of the fields to obtain rf signals that can be detected, processed, and used to reconstruct a useful image.
Similarly Positron Emission Tomography (PET) and other volumetric imaging technologies are useful for producing useful diagnostic renderings. One factor which can impair the usefulness of these volumetric imaging technologies, however, is the relative difficulty in discerning a structure of interest against an anatomical background with similar texture or contrast.
In particular, volumetric medical imaging technologies often rely on some form of automated segmentation to selectively extract an object from its background. However, segmentation algorithms which are designed for a large part of the human body or for the entire human body often perform poorly within local anatomical regions of complex anatomy. In particular, such segmentation algorithms are generally not optimized for local anatomical landscapes but are instead designed to accommodate wide anatomical variations. As a result, in regions where the anatomical landscape is distinctive, such algorithms may perform poorly. Instead, it may be desirable to employ customized algorithms within localized anatomical regions to obtain optimal processing within those regions.
Likewise, image acquisition, particularly where multiple acquisition events occur, may also benefit from customizing acquisition for localized anatomical variations. For example, anatomical regions which display little variability to a particular imaging modality may be scanned at a lower resolution or with thicker slices, thereby decreasing the acquisition time as well as the amount of data which must be generated and analyzed. Likewise, the region of interest or anatomically complex regions may benefit from increased resolution or thinner slices which yield greater data for analysis.
There is a need therefore, for a technique for automatically partitioning volumetric images into anatomically distinct sub-volumes which may then be differentially processed or acquired.